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Santos A, Leal GCL, Balancieri R. Identification of high-risk beneficiaries in private healthcare insurance. Health Informatics J 2024; 30:14604582241230384. [PMID: 38301111 DOI: 10.1177/14604582241230384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
The objective of this study was to apply the Knowledge Discovery in Databases process to find out if beneficiaries of a private healthcare insurance would belong, at least once, to the 'very high cost' and 'complex cases' groups throughout the 12 months after the month when algorithms were applied. Datasets were built containing information on beneficiaries' effective use of their health plan, as well as their characteristics. Five machine learning algorithms were used, namely Random forest, Extra tree, Xgboost, Naive bayes and K-nearest neighbor. The K-nearest neighbor algorithm had a recall rate of 81.12%, 83.77% precision and an Area Under the Curve (AUC) value of 0.9045. The study also revealed that categorization occurs, on average, 8.11 months before a beneficiary entering, for the first time, a high-risk group, considering the dataset classification from January 2019 to June 2020.
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Affiliation(s)
- Adauto Santos
- Technology Center, State University of Maringá, Maringá, Brazil
| | | | - Renato Balancieri
- Computer Science Collegiate, State University of Paraná, Apucarana, Brazil
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Nan J, Xu LQ. Designing Interoperable Health Care Services Based on Fast Healthcare Interoperability Resources: Literature Review. JMIR Med Inform 2023; 11:e44842. [PMID: 37603388 PMCID: PMC10477925 DOI: 10.2196/44842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 04/07/2023] [Accepted: 07/10/2023] [Indexed: 08/22/2023] Open
Abstract
BACKGROUND With the advent of the digital economy and the aging population, the demand for diversified health care services and innovative care delivery models has been overwhelming. This trend has accelerated the urgency to implement effective and efficient data exchange and service interoperability, which underpins coordinated care services among tiered health care institutions, improves the quality of oversight of regulators, and provides vast and comprehensive data collection to support clinical medicine and health economics research, thus improving the overall service quality and patient satisfaction. To meet this demand and facilitate the interoperability of IT systems of stakeholders, after years of preparation, Health Level 7 formally introduced, in 2014, the Fast Healthcare Interoperability Resources (FHIR) standard. It has since continued to evolve. FHIR depends on the Implementation Guide (IG) to ensure feasibility and consistency while developing an interoperable health care service. The IG defines rules with associated documentation on how FHIR resources are used to tackle a particular problem. However, a gap remains between IGs and the process of building actual services because IGs are rules without specifying concrete methods, procedures, or tools. Thus, stakeholders may feel it nontrivial to participate in the ecosystem, giving rise to the need for a more actionable practice guideline (PG) for promoting FHIR's fast adoption. OBJECTIVE This study aimed to propose a general FHIR PG to facilitate stakeholders in the health care ecosystem to understand FHIR and quickly develop interoperable health care services. METHODS We selected a collection of FHIR-related papers about the latest studies or use cases on designing and building FHIR-based interoperable health care services and tagged each use case as belonging to 1 of the 3 dominant innovation feature groups that are also associated with practice stages, that is, data standardization, data management, and data integration. Next, we reviewed each group's detailed process and key techniques to build respective care services and collate a complete FHIR PG. Finally, as an example, we arbitrarily selected a use case outside the scope of the reviewed papers and mapped it back to the FHIR PG to demonstrate the effectiveness and generalizability of the PG. RESULTS The FHIR PG includes 2 core elements: one is a practice design that defines the responsibilities of stakeholders and outlines the complete procedure from data to services, and the other is a development architecture for practice design, which lists the available tools for each practice step and provides direct and actionable recommendations. CONCLUSIONS The FHIR PG can bridge the gap between IGs and the process of building actual services by proposing actionable methods, procedures, and tools. It assists stakeholders in identifying participants' roles, managing the scope of responsibilities, and developing relevant modules, thus helping promote FHIR-based interoperable health care services.
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Affiliation(s)
- Jingwen Nan
- Health IT Research, China Mobile (Chengdu) Industrial Research Institute, Chengdu, China
| | - Li-Qun Xu
- Health IT Research, China Mobile (Chengdu) Industrial Research Institute, Chengdu, China
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Abid M, Schneider AB. Clinical Informatics and the Electronic Medical Record. Surg Clin North Am 2023; 103:247-258. [PMID: 36948716 DOI: 10.1016/j.suc.2022.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
The electronic medical record has fundamentally altered the way surgeons participate and practice medicine. There is now a wealth of data, once hidden behind paper records, that is, now available to surgeons to provide superior care to their patients. This article reviews the history of the electronic medical record, discusses use cases of additional data resources, and highlights the pitfalls of this relatively new technology.
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Affiliation(s)
- Mustafa Abid
- Department of Surgery, University of North Carolina, 101 Manning Drive, Chapel Hill, NC 27514, USA
| | - Andrew B Schneider
- Department of Surgery, University of North Carolina, 101 Manning Drive, Chapel Hill, NC 27514, USA.
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Lamo Y, Mukhiya SK, Rabbi F, Aminifar A, Lillehaug SI, Tørresen J, H Pham M, Côtè-Allard U, Noori FM, Guribye F, Inal Y, Flobakk E, Wake JD, Myklebost S, Lundervold AJ, Hammar A, Nordby E, Kahlon S, Kenter R, Sekse RJT, Griffin KF, Jakobsen P, Ødegaard KJ, Skar YS, Nordgreen T. Towards adaptive technology in routine mental health care. Digit Health 2022; 8:20552076221128678. [PMID: 36386244 PMCID: PMC9661551 DOI: 10.1177/20552076221128678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
This paper summarizes the information technology-related research findings after 5 years with the INTROducing Mental health through Adaptive Technology project. The aim was to improve mental healthcare by introducing new technologies for adaptive interventions in mental healthcare through interdisciplinary research and development. We focus on the challenges related to internet-delivered psychological treatments, emphasising artificial intelligence, human-computer interaction, and software engineering. We present the main research findings, the developed artefacts, and lessons learned from the project before outlining directions for future research. The main findings from this project are encapsulated in a reference architecture that is used for establishing an infrastructure for adaptive internet-delivered psychological treatment systems in clinical contexts. The infrastructure is developed by introducing an interdisciplinary design and development process inspired by domain-driven design, user-centred design, and the person based approach for intervention design. The process aligns the software development with the intervention design and illustrates their mutual dependencies. Finally, we present software artefacts produced within the project and discuss how they are related to the proposed reference architecture. Our results indicate that the proposed development process, the reference architecture and the produced software can be practical means of designing adaptive mental health care treatments in correspondence with the patients’ needs and preferences. In summary, we have created the initial version of an information technology infrastructure to support the development and deployment of Internet-delivered mental health interventions with inherent support for data sharing, data analysis, reusability of treatment content, and adaptation of intervention based on user needs and preferences.
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Affiliation(s)
- Yngve Lamo
- Department of Computer Science, Electrical Engineering, and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Suresh K Mukhiya
- Department of Computer Science, Electrical Engineering, and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Fazle Rabbi
- Department of Computer Science, Electrical Engineering, and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway
- Department of Information Science and Media Studies, Faculty of Social Science, University of Bergen, Bergen, Noway
| | - Amin Aminifar
- Department of Computer Science, Electrical Engineering, and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Svein I Lillehaug
- Department of Computer Science, Electrical Engineering, and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Jim Tørresen
- Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Minh H Pham
- Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Ulysse Côtè-Allard
- Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Farzan M Noori
- Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Frode Guribye
- Department of Information Science and Media Studies, Faculty of Social Science, University of Bergen, Bergen, Noway
| | - Yavuz Inal
- Department of Information Science and Media Studies, Faculty of Social Science, University of Bergen, Bergen, Noway
| | - Eivind Flobakk
- Department of Information Science and Media Studies, Faculty of Social Science, University of Bergen, Bergen, Noway
| | - Jo D Wake
- NORCE Norwegian Research Centre AS, Bergen, Norway
| | - Sunniva Myklebost
- Department of Biological and Medical Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
| | - Astri J Lundervold
- Department of Biological and Medical Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
| | - Aasa Hammar
- Department of Biological and Medical Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Emilie Nordby
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Smiti Kahlon
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Robin Kenter
- Department of Clinical Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
| | - Ragnhild JT Sekse
- Department of Clinical Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
| | | | - Petter Jakobsen
- Norment, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Ketil Joachim Ødegaard
- Norment, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | | | - Tine Nordgreen
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
- Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
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